It has been a demand, in recent years, to develop high-performance and low-cost semiconductor devices. For meeting this demand, accuracy of manufacturing process technologies for semiconductors is under improvement. Plasma etching is one of these manufacturing process technologies. According to plasma etching, processing shape dimensions, and quantitative prediction of crystal defect quantities caused by ion bombardment during processing (so-called damage quantities) are considered as important factors. For predicting the processing dimension shapes, a charging effect needs to be taken into consideration. The charging effect herein refers to generation of a potential distribution in the vicinity of a pattern surface in accordance with distribution differences of ions and electrons entering the processing pattern surface. This potential distribution varies transportation loci of ions and electrons, wherefore a side shape or the like gradually varies with development of processing. This varying effect of the side shape or the like in accordance with the variations of the loci of ions or the like is called a perturbation effect. The perturbation effect becomes particularly remarkable in fine transistor gate processing, or pattern processing at a high aspect ratio (i.e., narrow and deep pattern processing). Accordingly, shape or damage prediction considering the charging effect is regarded as an important factor in these types of processing.
There has been proposed a simulator which utilizes Monte Carlo method to predict the shape or damage in consideration of the foregoing charging effect (for example, see Non-patent Document 1). This simulator initially calculates transportation loci of ions and electrons by using Monte Carlo method to obtain a density distribution of ions and electrons. Subsequently, the simulator solves a Poisson equation on the basis of the obtained density distribution to derive a potential distribution on a pattern surface. Thereafter, the simulator again obtains transportation loci of ions and electrons under an effect of the potential distribution to obtain ion and electron densities on the pattern surface, and calculates an etch rate from the obtained ion and electron densities to predict a shape variation. In addition, a damage distribution caused by ultraviolet light, a variation of impurity concentrations, and others are also predicted as well as the shape variation. These procedures are repeated for each unit time until an etching end time to simulate an etching process.